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Direct Numerical Simulation of Complex Fuel Combustion with Detailed Chemistry: Physical Insight and Mean Reaction Rate Modeling


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Publication Date: 2015-06-30

Journal Title: Combustion Science and Technology

Publisher: Taylor & Francis

Volume: 187

Issue: 11

Pages: 1759-1789

Language: English

Type: Article

Metadata: Show full item record

Citation: Nikolaou, Z. M., & Swaminathan, N. (2015). Direct Numerical Simulation of Complex Fuel Combustion with Detailed Chemistry: Physical Insight and Mean Reaction Rate Modeling. Combustion Science and Technology, 187 (11), 1759-1789.

Description: This is the final version of the article. It first appeared from Taylor & Francis via http://dx.doi.org/10.1080/00102202.2015.1064911

Abstract: Direct numerical simulation of freely-propagating premixed flames of a multicomponent fuel is performed using a skeletal chemical mechanism with 49 reactions and 15 species. The fuel consists of CO,H2,H2O,CH4 and CO2 in proportions akin to blast furnace gas or a low calorific value syngas. The simulations include low and high turbulence levels to elucidate the effect of turbulence on realistic chemistry flames. The multi-component fuel flame is found to have a more complex structure than most common flames, with individual species reaction zones not necessarily overlapping with each other and with a wide heat releasing zone. The species mass fractions and heat release rate show significant scatter, with their conditional average however remaining close to the laminar flame result. Probability density functions of displacement speed, stretch rate, and curvature are near-Gaussian. Five different mean reaction rate closures are evaluated in the RANS context using these DNS data, presenting perhaps the most stringent test to date of the combustion models. Significant quantitative differences are observed in the performance of the models tested, especially for the higher turbulence level case.

Keywords: Direct Numerical Simulation, multi-component, detailed chemistry, combustion modelling, RANS

Sponsorship: ZMN and NS acknowledges the funding through the Low Carbon Energy University Alliance Programme supported by Tsinghua University, China. ZMN and NS also acknowledge Prof. S. Cant for the DNS code. ZMN acknowledges the educational grant through the A.G. Leventis Foundation. This work made use of the facilities of HECToR, the UK’s national high performance computing service, which is provided by UoE HPCx Ltd at the University of Edinburgh, Cray Inc and NAG Ltd, and funded by the Office of Science and Technology through EPSRC’s High End Computing Programme. EPSRC support is acknowledged.

Identifiers:

This record's URL: http://www.repository.cam.ac.uk/handle/1810/248829http://dx.doi.org/10.1080/00102202.2015.1064911

Rights: Creative Commons Attribution 4.0

Licence URL: http://creativecommons.org/licenses/by/4.0/





Autor: Nikolaou, Z. M.Swaminathan, N.

Fuente: https://www.repository.cam.ac.uk/handle/1810/248829



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